1. Field of the Invention
This invention relates generally to systems and methods for correction of scatter in images, and more specifically, to systems and methods for correction of scatter in images using a deconvolution procedure.
2. Background of the Invention
Computed tomography (CT) is an imaging technique that has been widely used in the medical field. In a procedure for computed tomography, an x-ray source and a detector apparatus are positioned on opposite sides of a portion of a patient under examination. The x-ray source generates and directs a x-ray beam towards the patient, while the detector apparatus measures the x-ray absorption at a plurality of transmission paths defined by the x-ray beam during the process. The detector apparatus produces a voltage proportional to the intensity of incident x-rays, and the voltage is read and digitized for subsequent processing in a computer. By taking thousands of readings from multiple angles around the patient, relatively massive amounts of data are thus accumulated. The accumulated data are then analyzed and processed for reconstruction of a matrix (visual or otherwise), which constitutes a depiction of a density function of the bodily section being examined. By considering one or more of such sections, a skilled diagnostician can often diagnose various bodily ailments such as tumors, blood clots, etc.
Computed tomography has found its principal application to examination of bodily structures or the like. When generating CT images, scatter effects due to various sources (such as body tissue with different thicknesses and/or densities, collimator and scintillator scatter, etc.) may be introduced into the images. In order to obtain a CT image with desirable quality, a deconvolution procedure can be performed to remove a scatter effect. For example, Fourier transform technique has been used to determine an inverse kernel K−1, where K is the kernel representing a scatter effect on an image data. However, the Fourier transform technique is cumbersome to implement, and may lead to inaccurate result—especially when an image contains noise or other discontinuities. Differential operator expansion technique has also been used. However, such technique is also difficult to implement, and is generally only applicable if the image data can be represented by a smooth function—which may not be desirable and may lead to inaccurate result in some cases.
For the foregoing reason, it would be desirable to have new systems and methods for correcting scatter in images.